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Since ancient times, human beings have had the universal law of “living by water”, and the Yangtze River plays a crucial role in promoting socioeconomic development. Impervious surface area (ISA) is the key indicator of urban expansion and can effectively reflect human activities. Therefore, based on long time-series data of ISA, we used the combination of remote sensing, geographical information systems, and spatial statistics to quantify the ISA spatiotemporal evolution patterns at different distances from different sections of the Yangtze River from 1990 to 2020 and proposed the ISA layered development model along riverbanks. The results indicate that the expansion rate of most cities along the Yangtze River had variations and different temporal characteristics among cities of different levels. From the perspective along the Yangtze River, there are certain regularities in the ISA growth. Human dependence on rivers has been decreasing over time, but the closer to the river, the greater the ISA expansion intensity (EI). The fluctuation trends of expansion intensity within different distance ranges (10–50 km) are similar in different sections over time and approximate to “a short head S-shaped curve”, but the size of EI varies in different sections along the Yangtze River. Different sections along the Yangtze River show the pattern of “slow-fast-deceleration, with the highest intensity occurring around 2015”. In the process of urbanization, areas far away from rivers will eventually connect with areas close to rivers, and the regional spatial pattern differences will gradually weaken. Multiple regression analysis indicated that the economic, social, and geographical factors were strongly associated with spatiotemporal differences in ISA expansion. This study will deepen our understanding of human activity changes along the Yangtze River, which is of great significance for implementing the national major strategy of “to step up conservation of the Yangtze River and stop its over development” and achieving the sustainable development between humans and water.

MAX phases and its derived two-dimensional MXenes have attracted considerable interest because of their rich structural chemistry and multifunctional applications. Lewis acid molten salt route provides an opportunity for structure design and performance manipulation of new MAX phases and MXenes, Although a series of new MAX phases and MXenes were successfully prepared via Lewis acid melt route in recent years, few work is explored on nitride MAX phases and MXenes. Herein, a new copper-based 413-type Ti4CuN3 MAX phase was synthesized through isomorphous replacement reaction using Ti4AlN3 MAX phase precursor in molten CuCl2. In addition, it was found that at high temperature Ti4N3Clx MXene will transform into two-dimensional cubic TiNα nanosheets with improved structural stability.

In DC microgrids, a large-capacity hybrid energy storage system (HESS) is introduced to eliminate variable fluctuations of distributed source powers and load powers. Aiming at improving disturbance immunity and decreasing adjustment time, this paper proposes active disturbance rejection control (ADRC) combined with improved MPC for n + 1 parallel converters of large-capacity hybrid energy storage systems. ADRC is utilized in outer voltage control loops, and improved MPC is employed in inner current control loops of n battery converters. Droop control is adopted to obtain power distribution between n battery converters, and a DC bus voltage compensator is used to compensate voltage deviations and maintain constant DC bus voltage. The low-pass filter (LPF) is adopted to obtain high-frequency power as the reference for the supercapacitor converter, ADRC is also utilized in the outer power control loop, and MPC is employed in the inner current control loop. Compared with traditional observers, the voltage expansion state observer of the proposed ADRC control is independent of the system model and parameters and consequently has strong disturbance immunity, and significantly reduces voltage overshoots during power fluctuations. The MPC-based inner current control loops of n + 1 converters accelerate current response speed and significantly decrease switching losses. Simulation and experimental results indicate that utilizing the proposed control strategies, large-capacity HESS has stronger anti-interference ability, shorter regulation time, smaller switching loss, and simultaneously maintains the stability of the DC bus voltage.

BackgroundLung cancer is one of the most dangerous cancers in the world. Most lung cancer patients are diagnosed in the middle and later stages, which can lead to poor survival rates. The development of lung cancer is often accompanied by abnormal expression of exosomal non-coding RNAs, which means that they have the potential to serve as noninvasive novel molecular markers for lung cancer diagnosis.MethodsFor this study, we conducted a comprehensive literature search in PubMed, Web of science, Science direct, Embase, Cochrane, and Medline databases, and by reviewing published literature, The diagnostic capacity of exosomal microRNAs (miRNAs), long-chain non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) for lung cancer was evaluated. Functional enrichment analysis of miRNA target genes was performed.ResultsThe study included 41 papers, a total of 68 studies. More than 60 miRNAs, 9 lncRNAs and 14 circRNAs were involved. The combined sensitivity and specificity were 0.83(95%CI, 0.80~0.86) and 0.83(95% CI,0.79~0.87); 0.71(95% CI,0.68~0.74) and 0.79(95%CI, 0.75~0.82); 0.79(95%CI,0.67~0.87) and 0.81(95%CI,0.74~0.86), and constructed overall subject operating characteristic curves with the summarized area under the curve values of 0.90, 0.82, and 0.86.ConclusionOur study shows that exosomes miRNAs, lncRNAs and circRNAs are effective in the diagnosis of lung cancer, providing evidence for studies related to novel lung cancer diagnostic markers.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023457087.

The construction sector is known for its dynamic nature, and numerous construction projects have failed to reach completion due to inadequate development of leadership. As a widely recognized leadership, transformational leadership has shown the positive relationship with project success. However, the mechanisms driving this relationship remain unclear in the context of construction projects. In response to this topic, by adopting the Input-Mediator-Outcome model, this study seeks to investigate the mediating effect of team flexibility and team agility between transformational leadership and project success in the context of construction projects. Data were collected through a survey from 306 construction project members. The Structural Equation Modeling method was employed to test the proposed model. The findings demonstrate that (1) transformational leadership positively impacts team flexibility and team agility; (2) team flexibility and team agility positively impact project success; (3) team flexibility shows a positive mediating effect between transformational leadership and project success; (4) team agility shows no mediating effect between transformational leadership and project success; and (5) team flexibility and team agility play serial mediating roles between transformational leadership and project success.

The current scenario sees over 60% of primary energy being dissipated as waste heat directly into the environment, contributing significantly to energy loss and global warming. Therefore, low-grade waste heat harvesting has been long considered a critical issue. Pyroelectric (PE) materials utilize temperature oscillation to generate electricity, while thermoelectric (TE) materials convert temperature differences into electrical energy. Nanostructured PE and TE materials have recently gained prominence as promising catalysts for converting thermal energy directly into chemical energy in a green manner. This short review provides a summary and comparison of catalytic processes initiated by PE and TE effects driven by waste thermal energy. The discussion covers fundamental principles and reaction mechanisms, followed by the introduction of representative examples of PE and TE nanomaterials in various catalytic fields, including water splitting, organic synthesis, air purification, and biomedical applications. Finally, the review addresses challenges and outlines future prospects in this emerging field.

Abstract Islanded AC–DC hybrid microgrids composed of new energy sources, constant power loads and energy storage system are typical non‐linear systems, and guaranteeing large signal stability is a key issue. In this paper, the non‐linear model of islanded AC–DC hybrid microgrids is established, and large signal stability criteria are obtained. Considering reference current limitation of the energy DC–AC converter, the derived large signal stability criterion gives important constraints on the constant power loads power, the power of energy storage unit, DC bus voltage, the inductor and equivalent resistance of the AC filter, DC capacitor, the proportional parameter of the inner current controller and the maximum instantaneous power of the DC–AC converter. The paper is summarized as follows. Firstly, the equivalent model of the AC–DC hybrid microgrids in DQ rotating frame is established. Then based on mixed potential theory, the mixed potential model is constructed, and large signal stability criterion is derived and optimized considering the reference current limitation of the DC–AC converter. Finally, the presented criterion is verified by simulation and experimental results.

The main features of a giant cell tumor of bone (GCTB) are frequent recurrence and aggressive osteolysis, which leads to a poor prognosis in patients. Although the treatment methods for a GCTB, such as scraping and resection, effectively inhibit the disease, the tendency toward malignant transformation remains. Therefore, it is important to identify new treatment methods for a GCTB. In this study, we first found high Siglec-15 expression in GCTB tissues, which was significantly associated with Campanacci staging and tumor recurrence. In Spearman’s analysis, Siglec-15 expression was significantly correlated with Ki-67 levels in tumor tissues. In vitro, the mRNA and protein levels of Siglec-15 were high in GCTB stromal cells (Hs737. T), and Siglec-15 knockdown inhibited the biological characteristics of GCTB stromal cells. The RNA sequencing results enabled a prediction of the downstream genes by using the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and MCODE analyses, and the findings showed that CXCL8 was significantly regulated by Siglec-15 and might be a promising downstream target gene of Siglec-15. Therefore, Siglec-15 may be a potential immunotherapy target for a GCTB.

Antimicrobial peptides (AMPs) are widely recognized as promising natural antimicrobial agents. Insects, as the group of animals with the largest population, have great potential as a source of AMPs. Thus, it is worthwhile to investigate potential novel AMPs from Protaetia brevitarsis Lewis larvae, which is a saprophagous pest prevalent in China. In this study, comparing the whole-genome sequence of Protaetia brevitarsis Lewis larvae with the Antimicrobial Peptide Database (APD3) led to the identification of nine peptide templates that were potentially AMPs. Next, based on the peptide templates, 16 truncated sequences were predicted to the AMPs by bioinformatics software and then underwent structural and physicochemical property analysis. Thereafter, candidate small-molecule AMPs were artificially synthesized and their minimal inhibitory concentration (MIC) values were assessed. A candidate peptide, designated FD10, exhibited strong antimicrobial activity against both bacteria and fungi comprising Escherichia coli (MIC: 8 μg/mL), Pseudomonas aeruginosa (MIC: 8 μg/mL), Bacillus thuringiensis (MIC: 8 μg/mL), Staphylococcus aureus (MIC: 16 μg/mL), and Candida albicans (MIC: 16 μg/mL). Additionally, two other candidate peptides, designated FD12 and FD15, exhibited antimicrobial activity against both E. coli (MIC: both 32 μg/mL) and S. aureus (MIC: both 16 μg/mL). Moreover, FD10, FD12, and FD15 killed almost all E. coli and S. aureus cells within 1 h, and the hemolytic effect of FD10 (0.31%) and FD12 (0.40%) was lower than that of ampicillin (0.52%). These findings indicate that FD12, FD15, and especially FD10 are promising AMPs for therapeutic application. This study promoted the development of antibacterial drugs and provided a theoretical basis for promoting the practical application of antimicrobial peptides in the Protaetia brevitarsis Lewis larvae.

The secretory insecticidal protein Sip1Ab and crystal protein Cry8Ca from Bacillus thuringiensis (Bt) are widely recognized for their coleopteran insecticidal activities. It is worthwhile to investigate the insecticidal mechanisms of these two proteins against Colaphellus bowringi Baly, which is a serious pest of cruciferous vegetables in China and other Asian countries. To that end, the genes encoding the Sip1Ab and Cry8Ca proteins were amplified from the strain QZL38 genome, then expressed in Escherichia coli, after which bioassays were conducted in C. bowringi larvae. After feeding these two proteins, the histopathological changes in the midguts of C. bowringi larvae were observed using transmission electron microscopy (TEM), and the Brush Border Membrane Vesicle (BBMV) was extracted for competition binding assays. TEM showed that ingestion of Sip1Ab caused a significant reduction in growth of the larvae, disruption of midgut microvilli, and expansion of intercellular spaces. Competition binding assays demonstrated that Sip1Ab bound to C. bowringi BBMV with a high binding affinity. However, a mixture of the two proteins in equal proportions showed no significant difference in insecticidal activity from that of Sip1Ab. These results could provide a molecular basis for the application of Sip1Ab in coleopteran insect control and contribute to the study of the Sip1Ab insecticidal mechanism as well.

Image super-resolution (SR), as one of the classic image processing issues, has attracted increasing attention from researchers. As a highly ill-conditioned, non-convex optimization issue, it is difficult for image SR to restore a high-resolution (HR) image from a given low-resolution (LR) instance. Recent researchers have tended to regard image SR as a regression task and to design an end-to-end convolutional neural network (CNN) to predict the pixels directly, which lacks inherent theoretical analysis and limits the effectiveness of the restoration. In this paper, we analyze image SR from an optimization perspective and develop a deep successive convex approximation network (SCANet) for generating HR images. Specifically, we divide non-convex optimization into several convex LASSO sub-problems and use CNN to adaptively learn the parameters. To boost network representation, we use residual feature aggregation (RFA) blocks and devise a spatial and channel attention (SACA) mechanism to improve the restoration capacity. The experimental results show that the proposed SCANet can restore HR images more effectively than other works. Specifically, SCANet achieves higher PSNR/SSIM results and generates more satisfying textures.

Modular input-series–output-parallel (ISOP) converters are very suitable for high-voltage and high-power applications. In order to ensure the normal operation of ISOP converters, it is necessary to realize the input-voltage and output-current equalization of each submodule. However, there are few studies on the input-voltage and output-current equalization performance of the ISOP system. In this paper, the input-voltage and output-current equalization characteristics of a Boost + LLC modular ISOP converter are studied based on the small-signal model. In this paper, the small-signal model of an ISOP system is first established, and then the input-voltage and output-current equalization performance of the ISOP system under the condition of inconsistent submodule parameters are analyzed. Finally, simulations and experiments are reported to verify the results. The experimental results show that the ISOP system composed of a Boost + LLC cascaded module has excellent voltage and current self-equalization performance.

Objectives The present study aimed to develop a gene signature based on the ESTIMATE algorithm in hepatocellular carcinoma (HCC) and explore possible cancer promoters. Methods The ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cells (TICs) in a cohort of HCC patients. The differentially expressed genes (DEGs) were screened by Cox proportional hazards regression analysis and protein–protein interaction (PPI) network construction. Cyclin B1 (CCNB1) function was verified using experiments. Results The stromal and immune scores were associated with clinicopathological factors and recurrence-free survival (RFS) in HCC patients. In total, 546 DEGs were up-regulated in low score groups, 127 of which were associated with RFS. CCNB1 was regarded as the most predictive factor closely related to prognosis of HCC and could be a cancer promoter. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analyses indicated that CCNB1 levels influenced HCC tumor microenvironment (TME) immune activity. Conclusions The ESTIMATE signature can be used as a prognosis tool in HCC. CCNB1 is a tumor promoter and contributes to TME status conversion.

Soil water content (SWC) is a crucial parameter in ecology, agriculture, hydrology, and engineering studies. Research on non-invasive monitoring of SWC has been a long-lasting topic in these fields. Ground penetrating radar (GPR), a non-destructive geophysical technique, has the advantages of high resolution, deep detection depth, and high efficiency in SWC measurements at medium scale. It has been successfully applied in field investigations. This paper summarizes the recent progress in developing GPR-based SWC measurement methods, including reflected wave, ground wave, surface reflection, borehole GPR, full waveform inversion, average envelope amplitude, and frequency shift methods. The principles, advantages, limitations, and applications of these methods are described in detail. A comprehensive technical framework, which comprises the seven methods, is proposed to understand their principles and applicability. Two key procedures, namely, data acquisition and data processing, are emphasized as crucial to method applications. The suitable methods that will satisfy diverse application demands and field conditions are recommended. Future development, potential applications, and advances in hardware and data processing techniques are also highlighted.

With greater power density, a hybrid power source that combines supercapacitors and batteries has a wide range of applications in pulse-operated power systems. In this paper, a supercapacitor/battery semi-active hybrid energy storage system (HESS) with a full current-type control strategy is presented. The studied HESS is composed of batteries, supercapacitors, and a bidirectional buck–boost converter. The converter is controlled such that supercapacitors supply load power pulses, and batteries provide the power in steady state. To realize the fast compensation of the supercapacitors to the load power pulses, a power distribution module based on hysteresis control theory is designed in the control system. Moreover, the control strategy does not require the model parameters of the converter and supercapacitors, so the control system is simplified. A complete configuration scheme and cost analysis of the proposed HESS are also presented. Obtained results show that the proposed supercapacitor/battery semi-active HESS has good performance in terms of dynamic response, weight, and energy utilization coefficient (EUC).

The belowground root zone of influence (ZOI) is fundamental to the study of the root–root and root–soil interaction mechanisms of plants and is vital for understanding changes in plant community compositions and ecosystem processes. However, traditional root research methods have a limited capacity to measure the actual ZOIs within plant communities without destroying them in the process. This study has developed a new approach to determining the ZOIs within natural plant communities. First, ground-penetrating radar (GPR), a non-invasive near-surface geophysical tool, was used to obtain a dataset of the actual spatial distribution of the coarse root system in a shrub quadrat. Second, the root dataset was automatically clustered and analyzed using the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm to determine the ZOIs of different plants. Finally, the shape, size, and other characteristics of each ZOI were extracted based on the clustering results. The proposed method was validated using GPR-obtained root data collected in two field shrub plots and one simulation on a dataset from existing literature. The results show that the shrubs within the studied community exhibited either segregated and aggregated ZOIs, and the two types of ZOIs were distinctly in terms of shape and size, demonstrating the complexity of root growth in response to changes in the surrounding environment. The ZOIs extracted based on GPR survey data were highly consistent with the actual growth pattern of shrub roots and can thus be used to reveal the spatial competition strategies of plant roots responding to changes in the soil environment and the influence of neighboring plants.

To analyze the root-soil water relationship at the stand level, we integrated ground-penetrating radar (GPR), which characterized the distribution of lateral coarse roots (>2 mm in diameter) of shrubs (Caragana microphylla Lam.), with soil core sampling, which mapped soil water content (SWC) distribution. GPR surveys and soil sampling were carried out in two plots (Plot 1 in 2017 and Plot 2 in 2018) with the same size (30 × 30 m2) in the sandy soil of the semi-arid shrubland in northern China. First, the survey area was divided into five depth intervals, i.e., 0–20, 20–40, 40–60, 60–80, and 80–100 cm. Each depth interval was then divided into three zones in the horizontal direction, including root-rich canopy-covered area, root-rich canopy-free area, and root-poor area, to indicate different surface distances to the canopy. The generalized additive models (GAMs) were used to analyze the correlation between root distribution density and SWC after the spatial autocorrelation of each variable was eliminated. Results showed that the root-soil water relationship varies between the vertical and horizontal directions. Vertically, more roots are distributed in soil with high SWC and fewer roots in soil with low SWC. Namely, root distribution density is positively correlated with SWC in the vertical direction. Horizontally, the root-soil water relationship is, however, more complex. In the canopy-free area of Plot 1, the root-soil water relationship was significant (p < 0.05) and negatively correlated in the middle two depth intervals (20–40 cm and 40–60 cm). In the same two depth intervals in the canopy-free area of Plot 2, the root-soil water relationship was also significant (p < 0.01) but non-monotonic correlated, that is, with the root distribution density increasing, the mean SWC decreased first and then increased. Moreover, we discussed possible mechanisms, e.g., root water uptake, 3D root distribution, preferential flow along roots, and different growing stages, which might lead to the spatially anisotropic relationship between root distribution and SWC at the stand level. This study demonstrates the advantages of GPR in ecohydrology studies at the field scale that is challenging for traditional methods. Results reported here complement existing knowledge about the root-soil water relationship in semi-arid environments and shed new insights on modeling the complex ecohydrological processes in the root zone.

In view of the fact that the current online virtual network embedding algorithms do not consider the fragment resources generated in the embedding process deeply enough, resulting in the problem that the acceptance ratio and the revenue to cost ratio are both low, a mathematical model for virtual network reconfiguration is constructed and a heuristic algorithm for fragment-aware virtual network reconfiguration (FA-VNR) is proposed. The FA-VNR algorithm selects the set of virtual nodes to be migrated according to the fragment degrees of the physical nodes, and selects the best virtual node migration scheme according to the reduction of the fragment degrees of the physical nodes as well as the reduction of the embedding cost of the embedded virtual networks. Extensive simulation results show that the proposed FA-VNR algorithm not only can obviously improve the acceptance ratio and the revenue to cost ratio of the current online virtual network embedding algorithm, but also has better optimization effect than the existing virtual network reconfiguration algorithm.

To improve the low acceptance ratio and revenue to cost ratio caused by the poor match between the virtual nodes and the physical nodes in the existing virtual network embedding (VNE) algorithms, we established a multi-objective optimization integer linear programming model for the VNE problem, and proposed a novel two-stage virtual network embedding algorithm based on topology potential (VNE-TP). In the node embedding stage, the field theory once used for data clustering was introduced and a node embedding function designed to find the optimal physical node. In the link embedding stage, both the available bandwidth and hops of the candidate paths were considered, and a path embedding function designed to find the optimal path. Extensive simulation results show that the proposed algorithm outperforms other existing algorithms in terms of acceptance ratio and revenue to cost ratio.

In this paper, a novel triple-permanent-magnet-excited vernier (TPMEV) machine with double-stator (DS) is proposed, of which the power density and the torque density are effectively improved to satisfy the operating requirements of low speed and high torque density for direct drive systems. Three sets of permanent magnets (PMs) are placed on the two stators and the rotor, respectively, and the magnetic fields excited by these PMs are modulated to effective magnetic field harmonics with low pole-pair numbers and high speeds based on bi-directional field modulation effect of the non-uniform airgap permeance. Then two sets of armature windings respectively accommodated in two stators are designed according to the effective magnetic field harmonics, thus achieving the coupling between the PM magnetic fields produced by three sets of PMs and armature windings. Firstly, the topology of the TPMEV-DS machine is introduced. Secondly, the airgap flux density of the machine is analyzed based on the equivalent magnetic circuit method, which proves the improvement potentiality of power density and torque density due to the bi-directional field modulation effect. Finally, the performance of the TPMEV-DS machine is calculated and analyzed by the finite element method, verifying the advantages of high power density and high torque density for the direct drive systems.